Jim Swanson, who became the CIO at Monsanto Co. in 2013, has a ready example of how digital technology is having a material effect on business operations. This year, Monsanto IT used machine learning and other digital capabilities to help the company dramatically reduce its global carbon footprint. But that is just one of many business outcomes Swanson foresees, as the 100-plus-year agribusiness embraces "decision science" -- defined as the application of business, math, technology, design thinking and behavioral science to make better decisions.

SearchCIO caught up with Swanson at the recent MIT Sloan CIO Symposium in Cambridge, Mass., where he talked about how the Monsanto IT department is disrupting business processes and about his efforts to build the IT department of the future. Below are excerpts from the interview; click on the player button to hear the interview in its entirety.

Talk about an exciting project Monsanto IT took on in 2016.

Jim Swanson: We've been digitizing our business -- commercial, supply chain, R&D. I'll give you a simple example out of supply chain. One of our goals in the company is sustainability. We said we would be carbon neutral by 2021. So, we looked at our supply chain, which was a big emitter of carbon and greenhouse gases, and we looked at our transportation logistics distribution where we distribute seeds around the world. We were able to reduce our carbon footprint [by] 2,500 tons and remove 1.4 million miles of trucks [from] the road by using machine learning [and] digital capabilities and understanding the best routing and logistics that we have.

What's been your biggest challenge this year?

Swanson: A challenge continues to be getting the data to where we need it to be to support our decision science and our models. We continually work on a change management curve with our business -- so, how do you apply decision science in all aspects of what we do. What's been exciting is that they have adopted decision science, and they have adopted these newer technologies to change and disrupt the way they operate. But it's always a challenge to be able to drive that through all levels of the organization.

How is Monsanto IT delivering decision science to the business?

Swanson: We moved IT from the back office to really be a front-office capability. [We are] no more important or less important than your researcher, your marketer, your supply chain person. We have a seat at the table, which is really important. And through that seat, we've actually been able to influence and disrupt business processes through data, through technology. So, we're not just about automating the way you do things today. We're actually about disrupting it and improving the way you can do it going forward.

Swanson: We did a really big pivot on the IT organization over the last two years -- we call it our IT operating model -- that highlighted the key skills we needed for a future IT organization: Your high-end software engineering, your high-end decision science, mathematics and modeling capabilities, [and] things like human-centered design. So [that we're] actually building a user-friendly environment.

As we continue to go out, the IT organization will continue to evolve. You're going to see more and more roles that have IT embedded in it -- whether you're a marketer or a supply chain professional or a researcher -- that's just going to become the norm. We're going be the enablers of that. But IT [will] continue to be distributed across all roles in every company.

What skills will be tough for future IT organizations to find? How are you attracting those skills to IT now?

Swanson: The decision science skill set is highly sought after. The high-end engineering skill set is sought after. But even there, we take creative approaches. We look at nontraditional backgrounds -- maybe you're a physics major, maybe you're an arts major, maybe you're an English major -- that actually has applicability to some of the skill sets we need in IT currently and in the future.

Human-centered design needs graphic and artist capabilities. A physics person or a chemistry person can learn machine learning or software engineering. By training them on those tools or capabilities, you're going to start to expand your base. Then you need a domain expertise: We're in agriculture, and so we take agronomists, we take Ph.D. geneticists, and we blend them with technologists. Together, that Agile/DevOps model of diverse skill sets bolsters what we need to do.

How much does your company rely on data to make business decisions?

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We are a science and IP based company thus we apply data and decision science as part of our core to enable business decisions. We also seek to democratize data making it available across traditional intra-company boundaries to unlock its value across the enterprise.